cobraxy: COBRAxy/utils/model_utils.py comparison

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-:ef3df9b697b1
+:96f512dff490
 pathway_data.append(row)
 return pd.DataFrame(pathway_data)
+def set_annotation_pathways_from_data(model: cobraModel, df: pd.DataFrame):
+"""Set reaction pathways based on 'Pathway_1', 'Pathway_2', ... columns in the dataframe."""
+pathway_cols = [col for col in df.columns if col.startswith('Pathway_')]
+if not pathway_cols:
+print("No 'Pathway_' columns found, skipping pathway annotation")
+return
+pathway_data = defaultdict(list)
+for idx, row in df.iterrows():
+reaction_id = str(row['ReactionID']).strip()
+if reaction_id not in model.reactions:
+continue
+pathways = []
+for col in pathway_cols:
+if pd.notna(row[col]) and str(row[col]).strip():
+pathways.append(str(row[col]).strip())
+if pathways:
+reaction = model.reactions.get_by_id(reaction_id)
+if len(pathways) == 1:
+reaction.annotation['pathways'] = pathways[0]
+else:
+reaction.annotation['pathways'] = pathways
+pathway_data[reaction_id] = pathways
+print(f"Annotated {len(pathway_data)} reactions with pathways.")
 def build_cobra_model_from_csv(csv_path: str, model_id: str = "new_model") -> cobraModel:
 """
 Build a COBRApy model from a tabular file with reaction data.
 # set objective function
 set_objective_from_csv(model, df, obj_col="ObjectiveCoefficient")
 set_medium_from_data(model, df)
+set_annotation_pathways_from_data(model, df)
 print(f"Model completed: {len(model.reactions)} reactions, {len(model.metabolites)} metabolites")
 return model

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